Eco-efficiency characterization tool

ABSTRACT

A method includes determining, by a processing device, a first eco-efficiency characterization associated with a first design of manufacturing equipment based on one or more of water eco-efficiency characterization, emissions eco-efficiency characterization, or electrical energy eco-efficiency characterization. The water eco-efficiency characterization, the emissions eco-efficiency characterization, the electrical energy eco-efficiency characterization, and the first eco-efficiency characterization are associated with an amount of environmental impact generated by the manufacturing equipment per unit product produced by the manufacturing equipment. The method further includes comparing the first eco-efficiency characterization to a second eco-efficiency characterization that is associated with a second design of the manufacturing equipment. The method further includes implementing the second design of the manufacturing equipment responsive to determining, based on the comparing, that the second eco-efficiency characterization is associated with a lower amount of environmental impact per unit product than the first eco-efficiency characterization.

RELATED APPLICATION

This application is a continuation application of U.S. patentapplication Ser. No. 15/134,234, filed Apr. 20, 2016, the entire contentof which is hereby incorporated by reference herein.

FIELD OF THE INVENTION

Embodiments of the present invention generally relate to manufacturingequipment eco-efficiency characterization and optimization.

BACKGROUND OF THE INVENTION

The continued demand for electronic devices calls for an increasinglylarger demand for semiconductor wafers. The increase in manufacturing toproduce these wafers takes a substantial toll on the environment in theform of resource utilization and the creation of environmentallydamaging waste. Thus, there is an increased demand for moreecologically-friendly and environmentally responsible methods of wafermanufacture and of manufacturing in general.

SUMMARY

The following is a simplified summary of the disclosure in order toprovide a basic understanding of some aspects of the disclosure. Thissummary is not an extensive overview of the disclosure. It is notintended to delineate any scope of the particular implementations of thedisclosure or any scope of the claims. Its sole purpose is to presentsome concepts of the disclosure in a simplified form as a prelude to themore detailed description that is presented later.

Embodiments of the present invention provide improved methods, systemsand software for eco-efficiency characterization.

In one embodiment, eco-efficiency characterization includes receiving,by a processing device, a selection of a manufacturing equipment andutility use data associated with the manufacturing equipment. In oneembodiment, the utility use data includes water usage data, gas usagedata, and electrical energy usage data. Utility use data may alsoinclude data associated with liquid process chemicals. Utilization dataassociated with a processing time and an idle time of the manufacturingequipment may also be received.

Eco-efficiency characterization may also include calculating a watereco-efficiency characterization, an emissions eco-efficiencycharacterization, and an electrical energy eco-efficiencycharacterization based on the first utility use data and the firstutilization data.

A combined eco-efficiency characterization may be calculated based onthe water, emissions, and electrical energy eco-efficiencycharacterizations and the first utilization data. The water, emissions,electrical energy, and combined eco-efficiency characterizations may beassociated with a per-unit amount of environmental impact generated bythe manufacturing equipment. Additionally, the eco-efficiency model mayinclude providing at least one of the water, emissions, electricalenergy, and combined eco-efficiency characterizations for display by agraphical user interface (GUI).

In another embodiment, eco-efficiency characterization may includereceiving, by a processing device of a manufacturing equipment, a firsteco-efficiency characterization of the manufacturing equipment anddetermining utility use data associated with the manufacturingequipment, the utility use data including: water usage data, gas usagedata, and electrical energy usage data. In one embodiment, the firsteco-efficiency characterization may be received from the manufacturingequipment itself. In another embodiment, the first eco-efficiencycharacterization may be received from a server associated with themanufacturing equipment. First utilization data associated with aprocessing time and an idle time of the manufacturing equipment may alsobe determined. First utilization data may also include process andproduct information associated with the manufacturing equipment.

The processing device of the manufacturing equipment may determine anadjustment to one or more settings associated with the manufacturingequipment, the one or more settings based on the first use data, firstutilization data, and first eco-efficiency characterization. Theadjustment to the one or more settings may cause an increase in theper-unit eco-efficiency of the manufacturing equipment. The processingdevice of the manufacturing equipment may further implement theadjustment to the one or more settings associated with the secondeco-efficiency characterization on the manufacturing equipment.

Furthermore, embodiments of the present disclosure relate to aneco-efficiency characterization system including a memory to store theselection of a manufacturing equipment, first utility use data and firstutilization data associated with the manufacturing equipment, and thefirst, second, third, and combined eco-efficiency characterizations anda processing device, operatively coupled to the memory. In oneembodiment the processing device is to perform the operations listedabove. In another embodiment, a non-transitory machine-readable storagemedium includes instructions that, when accessed by a processing device,cause the processing device to perform the above operations.

BRIEF DESCRIPTION OF THE DRAWINGS

Various embodiments of the present invention will be understood morefully from the detailed description given below and from theaccompanying drawings of various embodiments of the invention.

FIG. 1 illustrates an example architecture of a per-unit eco-efficiencycharacterization system, in accordance with an embodiment of the presentinvention.

FIG. 2A is an example block diagram of an eco-efficiency analyzer, inaccordance with an embodiment of the present invention.

FIG. 2B is a block diagram of an equipment controller, in accordancewith an embodiment of the present invention.

FIG. 3 is a flow diagram illustrating a method for eco-efficiencycharacterization, in accordance with an embodiment of the presentinvention.

FIG. 4 is a flow diagram illustrating a method for on-equipmenteco-efficiency characterization, in accordance with an embodiment of thepresent invention.

FIG. 5 is a block diagram of a multicomponent manufacturing equipmentsystem, in accordance with an embodiment of the present invention.

FIG. 6 is a block diagram of a per-unit eco-efficiency characterizationsystem, in accordance with an embodiment of the present invention.

FIG. 7 is a block diagram of an example computer system that may performone or more of the operations described herein.

DETAILED DESCRIPTION

Ecological-efficiency (eco-efficiency) characterization is a complextechnique used to determine how different levels of inputs (e.g.,resources, utilization, etc.) associated with a particular manufacturingtool during use of the tool impact eco-efficiency of the manufacturingtool. Eco-efficiency characterization may be beneficial duringdevelopment of a manufacturing tool to help develop manufacturing toolsthat maximize a per-unit (or per-time) eco-efficiency and minimizeharmful environmental impact. Eco-efficiency characterization may alsobe beneficial after tool development, while the tool is operational, tofine tune the per-unit eco-efficiency characteristics of the tool inview of the specific parameters according to which the tool isoperating.

Embodiments described herein provide a system for systematicallyperforming eco-efficiency characterization of a manufacturing toolthroughout the design, development and manufacturing process of thattool. Additionally, embodiments further provide a system that is able torefine the eco-efficiency of a manufactured tool during use.

In some embodiments, eco-efficiency is calculated on a per-unit basis.Typically, per-unit eco-efficiency is not taken into account in themanufacturing tool development process. Additionally, it can be acumbersome and complicated process to characterize per-uniteco-efficiency to adjust settings on a manufacturing tool while thattool is in use (e.g., while a tool is used for wafer production).Furthermore, prior solutions used special eco-efficiency training andspecialized engineers and analysts for eco-efficiency characterizationanalysis. Embodiments of the present disclosure provide improvedmethods, systems and software for eco-efficiency characterization on aper-unit basis.

In one embodiment, per-unit eco-efficiency characterization may beperformed by a software tool in all stages of manufacturing equipmentlifecycle, including during the design stages and the operational stagesof wafer manufacturing equipment. Eco-efficiency may be the amount ofenvironmental resource (e.g., electrical energy, water, gas, etc.)consumed per unit of equipment production. Eco-efficiency may also becharacterized as the amount of environmental impact (e.g., CO₂emissions, heavy metal waste, etc.) generated per unit of equipmentproduction.

Per-unit analysis, where a unit is any measurable quantity (e.g., asubstrate (wafer), die, area (cm²), time period, device, etc.) operatedon by a manufacturing tool, allows for more precise characterizations.Eco-efficiency on a “per-unit” basis allows for an accuratedetermination of resource usage and environmental impact per-unitproduced, and can be easily manipulated as a measure of value. Forexample, it may be determined that a particular manufacturing tool hasan electrical energy per-wafer-pass eco-efficiency rating of 1.0-2.0 kWhper wafer pass (in other embodiments eco-efficiency ratings may be lessthan 0.5 kWh, up to 20 kWh, or even greater than 20 kWh per wafer pass),indicating that each wafer operated on by the manufacturing tool mayuse, for example, 1.0-2.0 kWh of electrical energy per wafer pass. Inother embodiments various other amounts of electrical energy may beused. Determining eco-efficiency on a per-wafer-pass basis allows foreasy comparison with other manufacturing tools that have a differentyearly electrical energy consumption value due to variance in yearlywafer throughput. In one embodiment, eco-efficiency may also bedetermined on a per-device basis by dividing a per-wafer eco-efficiencycharacterization by the number of devices per wafer.

Performing per-unit eco-efficiency characterization during the earlydesign stages of equipment manufacturing allows designers to makebetter, more eco-efficient design choices at minimal cost.Eco-efficiency may be manipulated and improved early on in the designstages of manufacturing equipment. Eco-efficiency characterization earlyon in the design process may allow for better, more eco-friendlycomponent selection, subsystem design, system integration, processdesign, process materials selection, and system configuration.

In one embodiment, multiple designers may have parallel access to adatabase of already calculated eco-efficiency models for specificequipment or subcomponents. The designers may produce prospectivedesigns by selecting and adding together one or more subcomponents, eachof which may have their own respective eco-efficiency models. Thecombined eco-efficiency models of all of the subcomponents may then becombined to produce an overall eco-efficiency model for a prospectivedesign. The prospective design and its eco-efficiency model and theeco-efficiency models of it subcomponents may be stored in a database.

At any time in the development process for a tool, an engineer may altera configuration of that tool, which may cause a change in theeco-efficiency model for that tool. The changes to the configuration andthe resulting changes to the eco-efficiency model may be stored in thedatabase. In this way, per-unit eco-efficiency characterization iscollaborative, allowing equipment designers to benefit from each other'swork. In one embodiment, designers may see updates to manufacturingequipment design in real-time, as changes associated with eco-efficiencyare made. Designers may select the equipment or subcomponents with thedesired eco-efficiency for the desired application. Furthermore,per-unit eco-efficiency may be calculated for manufacturing equipmentbased on known per-unit eco-efficiency characterizations forsubcomponents. Such known per-unit eco-efficiency characterizations forsubcomponents may be stored in a database. In another embodiment,per-unit eco-efficiency may be calculated for manufacturing equipmentbased combined utility and utilization data for each of thesubcomponents of the manufacturing equipment.

Components and subcomponents may be compared and contrasted. If aneco-efficiency model does not already exist for a particular equipmentor subcomponent, the designer may perform an eco-efficiency analysis onthe equipment, and store the resulting eco-efficiency model in thedatabase. Designers may have the option to save various versions ofequipment in development, with each version having an associatedeco-efficiency model. In this way, versioning is traceable andeco-efficiency may be optimized by determining the equipment designversion with the desired eco-efficiency.

Manufacturing equipment and subsystems are sometimes used in a varietyof applications, each application having its own eco-efficiency. In sucha situation, multiple per-unit eco-efficiency characterizations for thesame equipment or subcomponent to be used under different conditions maybe stored in a database. When a designer selects the appropriateequipment from the database, he may be presented with a variety ofapplications for the equipment, each with its own per-uniteco-efficiency characterization. Furthermore, a designer is able toselect equipment from the database to use as a starting point for a newapplication that does not yet exist in the database. The designer maymodify the parameters of the equipment to match the appropriateapplication, perform a per-unit eco-efficiency characterization, andstore the result back to the database.

In another embodiment, per-unit eco-efficiency characterization may beperformed on manufacturing equipment itself during operation. Themanufacturing equipment may access real-time variables, such asutilization and utility use data of the equipment, and use the real-timevariables in the eco-efficiency model. In this embodiment, manufacturingequipment may fine-tune settings on the equipment to maximizeeco-efficiency in view of the current operating conditions of themanufacturing equipment. On-equipment eco-efficiency characterizationmay be beneficial to fine-tune the eco-efficiency of manufacturingequipment that was designed using theoretical, averaged, or expectedvariable conditions.

Described are embodiments of methods and systems that perform per-uniteco-efficiency characterization of wafer manufacturing equipment. Byperforming per-unit eco-efficiency characterization in the design andoperational stages of equipment, the eco-efficiency of the equipment canbe maximized.

FIG. 1 illustrates an example architecture of a per-unit eco-efficiencycharacterization system. In one embodiment, the per-unit eco-efficiencycharacterization system 100 may include a computing device 102, datastore 108, manufacturing equipment 112, 116, and sub-fab front endcontroller 120 with associated sub-fab auxiliary systems 122-128.

The manufacturing equipment 112, 116 may be semiconductor wafermanufacturing equipment that includes one or more processing chambers.For example, the manufacturing equipment 112, 116 may be any combinationof an ion implanter, an etch reactor (e.g., a processing chamber), aphotolithography device, a deposition device (e.g., for performingchemical vapor deposition (CVD), physical vapor deposition (PVD),ion-assisted deposition (IAD), and so on), or any other combination ofmanufacturing devices.

In one embodiment, the manufacturing equipment 112, 116 is connected todata store 108, sub-fab front end controller 120 and computing device102 via network 106. The network 106 may be a local area network (LAN),and may be part of an equipment automation layer that may additionallyinclude routers, gateways, servers, data stores, and so on. Themanufacturing equipment 112, 116 may connect to the equipment automationlayer (e.g., to the network 106) via a SEMI Equipment CommunicationsStandard/Generic Equipment Model (SECS/GEM) interface, via an Ethernetinterface, and/or via other interfaces. In one embodiment, the equipmentautomation layer enables process data (e.g., data collected bymanufacturing equipment 112, 116 during a process run) to be stored indata store 108.

In other embodiments, manufacturing equipment 112, 116 may connectdirectly to data store 108, sub-fab front end controller 120 and/orcomputing device 102. In one embodiment, manufacturing equipment 112,116 may include equipment controllers 114, 118.

In one embodiment, equipment controllers 114, 118 determine the per-uniteco-efficiency models of associated manufacturing equipment 112, 116during operation. Equipment controllers 114, 118 may also adjustsettings associated with the manufacturing equipment 112, 116 based onthe determined eco-efficiency models so as to optimize theeco-efficiency of the equipment 112, 116 in light of the currentmanufacturing conditions.

In one embodiment, equipment controllers 114, 118 may include a mainmemory (e.g., read-only memory (ROM), flash memory, dynamic randomaccess memory (DRAM), static random access memory (SRAM), etc.), and/ora secondary memory (e.g., a data storage device such as a disk drive).The main memory and/or secondary memory may store instructions forperforming various types of manufacturing processes.

The equipment controllers 114, 118 may also include a processing devicecoupled to the main memory and/or secondary memory (e.g., via a bus) toexecute the instructions. The processing device may be a general-purposeprocessing device such as a microprocessor, central processing unit, orthe like. The processing device may also be a special-purpose processingdevice such as an application specific integrated circuit (ASIC), afield programmable gate array (FPGA), a digital signal processor (DSP),network processor, or the like. In one embodiment, equipment controllers114, 118 are programmable logic controllers (PLCs).

In one embodiment, equipment controllers 114, 118 may determine anactual eco-efficiency characterization associated with the manufacturingequipment based on first utility use data associated with themanufacturing equipment and first utilization data associated with themanufacturing equipment. The first utility use data and firstutilization data may be determined by the equipment controllersthemselves. In another embodiment, the first utility use data and firstutilization data are received from an external source (e.g., computingdevice 102). Equipment controllers 114, 118 may compare the actualeco-efficiency characterization to a first eco-efficiencycharacterization associated with the manufacturing equipment. Theeco-efficiency characterizations may be different when different use andutilization data values were used to compute the first eco-efficiencycharacterization than the actual values associated with the operatingmanufacturing device.

In one embodiment, equipment controllers 114, 118 may determine that thefirst eco-efficiency characterization is more eco-efficient than theactual eco-efficiency characterization, indicating that it may bepossible to adjust settings on the manufacturing equipment to betteroptimize the manufacturing equipment for eco-efficiency. In someembodiments, manufacturing equipment may control and adjust subcomponentsettings to better optimize eco-efficiency.

Equipment controllers 114, 118 may also determine based on the actualuse data, actual utilization data, and an eco-efficiencycharacterization that the actual use data or the actual utilization datais not the same as use data and utilization data associated with thefirst eco-efficiency characterization. This may be the case when nominalor estimated data values are used to determine the first eco-efficiencycharacterization and different, actual recorded data values are usedwhile the manufacturing equipment is in operation. In such a scenario,an adjustment to one or more settings associated with the manufacturingequipment may be beneficial to optimize the eco-efficiency of themanufacturing equipment.

The per-unit eco-efficiency characterization system 100 may furtherinclude one or more sub-fab auxiliary systems 122-128 connected to thenetwork 106 via sub-fab front end controller 120. In alternativeembodiments, the per-unit eco-efficiency characterization system 100 mayinclude more or fewer components. For example, the per-uniteco-efficiency characterization system 100 may include manually operated(e.g., off-line) manufacturing equipment and sub-fab auxiliary systemsthat are not connected to network 106.

In one embodiment, sub-fab front-end controller 120 is a controllersuitable to control the sub-fab auxiliary systems 122-128. In oneembodiment, sub-fab front-end controller 120 may include a main memory(e.g., read-only memory (ROM), flash memory, dynamic random accessmemory (DRAM), static random access memory (SRAM), etc.), and/or asecondary memory (e.g., a data storage device such as a disk drive). Themain memory and/or secondary memory may store instructions forperforming various types of manufacturing processes.

The sub-fab front-end controller 120 may also include a processingdevice coupled to the main memory and/or secondary memory (e.g., via abus) to execute the instructions. The processing device may be ageneral-purpose processing device such as a microprocessor, centralprocessing unit, or the like. The processing device may also be aspecial-purpose processing device such as an application specificintegrated circuit (ASIC), a field programmable gate array (FPGA), adigital signal processor (DSP), network processor, or the like. In oneembodiment, sub-fab front-end controller 120 is a programmable logiccontroller (PLC).

In one embodiment, sub-fab auxiliary systems 122-128 may also each havea controller (not shown). Sub-fab auxiliary systems 122-128 may includeabatement tools, ac power distributors, primary vacuum pumps, sparevacuum pumps, water pumps, chillers, heat exchangers, process coolingwater supplies and delivery systems, etc. In other embodiments, toolslike those just described may be considered part of the manufacturingequipment itself and may communicate with equipment controllers 114, 118directly.

The per-unit eco-efficiency characterization system 100 may furtherinclude a data store 108 with associated database 110 to store per-uniteco-efficiency models of manufacturing equipment 112, 116 and/or sub-fabauxiliary systems 122-128. Furthermore, database 110 may store per-uniteco-efficiency models associated with manufacturing equipment andsubcomponents not associated with system 100. Additionally, the per-uniteco-efficiency characterization system 100 may include one or morecomputing devices (e.g., computing device 102) connected to the network106.

In one embodiment, computing device 102 includes an eco-efficiencyanalyzer 104. Eco-efficiency analyzer 104 of computing device 102determines the per-unit eco-efficiency of manufacturing equipmentalready existing (e.g., manufacturing equipment 112, 116) and/ormanufacturing equipment that is currently being designed.

Eco-efficiency characterization determinations made by eco-efficiencyanalyzer 104 may be used to determine more eco-efficient settings forexisting manufacturing equipment 112, 116. Determined settings may besent to manufacturing equipment 112, 116 via network 106 to beimplemented. Eco-efficiency characterization determinations made byeco-efficiency analyzer 104 may also be used to influence designchoices, so as to optimize eco-efficiency when new manufacturingequipment is being designed.

FIG. 2A is an example block diagram of an eco-efficiency analyzer 104,in accordance with an embodiment of the present invention. In oneembodiment, eco-efficiency analyzer 104 includes eco-efficiencycharacterizer for water usage 202, eco-efficiency characterizer foremissions 204, eco-efficiency characterizer for electrical energy usage206, and combined eco-efficiency characterizer 208. In otherembodiments, eco-efficiency analyzer may include characterizers forother categories, such as gas usage, heavy metals, and eutrophicationpotential. In one embodiment, computing device 102 includeseco-efficiency analyzer 104. This arrangement of modules may be alogical separation, and in other embodiments, these modules or othercomponents can be combined together or separated into furthercomponents.

In one embodiment, eco-efficiency characterizers 202-206 determineper-unit eco-efficiency characterizations for each of the respectiveutilities consumed, or waste streams generated (e.g., heavy metals,eutrophication agents, ozone depleters), by the associated manufacturingequipment (e.g., water, process emissions, electrical energy, etc.).Characterizers 202-206 may receive inputs associated with manufacturingequipment on which to base a per-unit eco-efficiency characterization.Examples of inputs may include: how much of each respectiveutility/resource/waste the manufacturing equipment consumes orgenerates, equipment configuration information, component efficiency,process recipes and materials, throughput and/or product information,and utilization (up-time vs. down-time of manufacturing equipment). Inone embodiment, the characterizers may be provided with measured,nominal, or estimated values for each of the above inputs.

Eco-efficiency characterizers 202-208 may produce eco-efficiencycharacterizations associated with each of their respective utilities(e.g., water, process emissions, and electrical energy) based on totalequivalent use under the SEMI S23 protocol, extensions of the protocol,summations of gas uses, and/or Process Conversion Factors. In otherembodiments, eco-efficiency characterizers for other types of resources(e.g. solids and/or liquid chemicals consumed) may exist.

SEMI S23 is a semiconductor industry standard for measuring, analyzing,reporting and reducing electrical energy requirements and energyconservation for a piece of manufacturing equipment. SEMI S23 defines amethod for estimating all of the energy that a particular manufacturingequipment will consume while in use and while idle. This may includeelectrical energy supplied directly to the equipment and electricalenergy consumed to provide non-electrical utilities (water, exhaust,etc.). The S23 protocol may be extended in embodiments to includenatural gas and other non-electrical energy use. To estimate the energyused to supply non-electrical utilities to a tool, a set of EnergyConversion Factors (ECFs) may be used. Process Conversion Factors mayalso be defined and used to estimate process emissions from a process onthe basis of the process type and the amounts and types of inputmaterials to the process. One example may be a reactor that burnsmethane, CH₄, with oxygen, O₂, to form carbon dioxide, CO₂, and water,H₂O according to the reaction CH₄+2O₂→CO₂+2 H₂O. In the presence ofsufficient oxygen and in an entirely efficient reactor, each unit moleor unit volume of CH₄ input may result in the production of one mole orunit volume of CO₂ and two moles or units volume of H₂O. In thisreactor, the process conversion factor for CH₄→CO₂ may be 1 and theprocess conversion factor for CH₄ to H₂O may be 2. Worth mentioning hereis that these are not the theoretical stoichiometric ratios of thereaction, but that they are what is actually occurring in the particularreactor. For any number of reasons (e.g., some methane is absorbed intoreactor walls, insufficient O₂, contaminants reacting with some of theCH₄ to form other by-products than CO₂ and H₂O, etc.) the actualparticular reactor may produce actual CO₂ and H₂O emissions in ratiosassociated with amount of input CH₄ other than 1 and 2, respectively. Inother embodiments, there may be other predictable by-products that canbe assigned PCFs. The PCFs for a process may be specific to the processand may be the values that are known by experimentation or other methodto actually represent the process.

In one embodiment, Energy Conversion Factors (ECFs) may have the generalform:

ECF_(utilityX)=electrical energy (kWh)/unity of utility X

For example, the SEMI S23-0708 ECF for deionized (DI) water (UPW) at <25C is:

ECF_(UPW<25C)=9.0 kWh/m³ of DI Water

In other words, every 1000 L (m³) of DI water used by an equipment adds9.0 kWh to the equipment's equivalent energy consumption.

The basic steps of an electrical energy usage analysis as part of aper-unit eco-efficiency characterization might include:

-   -   1. Define the scope of the product to be evaluated. This        includes determining exactly what hardware is to be        characterized. If the object being characterized is a system, it        may include determining peripheral equipment such as vacuum        pumps and/or abatement to be part of the system or,        alternatively, analyzed separately.    -   2. Select a baseline recipe or process for the evaluation. This        may include selecting the recipes and other process        specifications that determine the particular application of the        equipment for which the characterization will apply. These        recipes and processes may determine the use rates of the input        utilities (e.g., direct electricity, cooling water, N2, CDA,        exhaust, vacuum, etc.).    -   3. Measure (or estimate) the power and utility consumption while        idle and while processing. This may include either measuring or        estimating the input utility use rates associated with the        recipes and processes selected. SEMI S23 determines equivalent        electrical energy requirements for both the processing and idle        states, so input utility use rates should be provided for both        of those states or, potentially, other states. Once input        utility use rates are available, the energy conversion factors        (or their rate equivalents) may be applied to the input        utilities to calculate equivalent energy use rate in step 4.    -   4. Use the measured (or estimated) power and utility consumption        and the ECFs to calculate the total amount of energy that an end        user must consume to operate the tool.    -   5. Normalize the results to energy per unit product, for        example: kWh/wafer-pass or kWh/cm². This may include the        amortization of the idle equivalent energy consumption into the        per-unit consumption. For example, if the tool is idle for one        hour for every 10 hours that it processes, the equivalent energy        consumed in one hour of idle period can be amortized into the        number of units produced in the 10 hours of processing.        ECFs may take into account process materials and energy consumed        in the supply-chain, before wafer manufacture occurs.        Furthermore, Process Conversion Factors may be extended (e.g.,        as water conversion factors) to estimate the amount of water        consumed by and emissions produced by manufacturing equipment.        ECFs may be defined for industrial water, drains, and natural        gas. In one embodiment, energy balance calculations may be        embedded into the eco-efficiency characterization to calculate        energy loses to ambient air, energy, and the water requirements        for HVAC. Process Conversion Factors and abatement Destruction        Removal Efficiencies (DREs) may be used to convert process        material and process recipe information into pre and post        abatement process emissions characterizations.

The DREs may be rates, expressed as percent of complete removal orconversion, that the abatement process either removes harmful emissionsor converts harmful emissions (e.g., as estimated by an eco-efficiencycharacterizer for emissions using PCFs) into less harmful emissions(e.g., CO₂ and inert or common atmospheric gases). For example, aprocess may produce emissions of C₂F₆, a Greenhouse Gas, which may havea Global Warming Potential (GWP) of 9,200, that is, 9200 times theeffect of CO₂ (GWP=1). A wet-burn abatement system, that is, one thatuses combustion of a fuel gas and a wet scrubber, may be employed toconvert the C₂F₆ into gaseous CO₂ and Hydrofluoric Acid, HF (or otherdissolved Fluorine compounds), which can be removed in the wet effluentfrom the scrubber. If the abatement is 100% efficient (DRE=100%), all ofthe C₂F₆ is converted to CO₂ emitted as the more relatively benignproduct of abatement, and HF (or other dissolved Fluorine compounds)removed in the wet effluent and disposed of in a safe manner. Abatementprocesses may not be, however, 100% efficient. If 1% of the input C₂F₆in a particular abatement process passes through un-abated, theabatement process has a DRE of 99%. The actual post-abatement amounts ofunabated input materials and abatement-generated CO₂ can also becalculated using the molecular weights of the pre-abatement gases, thepre-abatement gas flows, the DREs, and the molecular weights andformulae of the input gases. Equivalent CO₂ pre- and post-abatement canalso be calculated. In the example of C₂F₆ above, a kilogram of C₂F₆prior to abatement may have the equivalent global warming effect of 9200kg of equivalent CO₂ (9200 kgCO2e). If the abatement is 99% efficient(DRE=99%), the output of the abatement may be 0.01 kg C₂F₆ (equivalentglobal warming impact of 0.01×9200=92 kgCO2e) along with[(0.99×2×44)/138]=0.63 kg CO₂ for a total post abatement global warmingimpact of 92.63 kgCO2e. 44 and 138 are the molecular weights of CO₂ andC₂F₆, respectively, and the 2 is the ratio of the amount of carbon inone mole of C₂F₆ to that in one mole of CO₂.

In one embodiment, process recipes may be input to the per-uniteco-efficiency characterizations. A process recipe may specify time,power, flow, temperature, etc. to produce the desired result. Suchprocess recipes may affect the eco-efficiency characterization of themanufacturing equipment. A process recipe input to a per-uniteco-efficiency characterization may be analyzed according to thefollowing example method:

-   -   1. Examine the recipe first (or next) step.    -   2. Determine the step time and output value from the recipe        step. In one embodiment the output parameter represents a        physical parameter specified for control by the recipe. For        example, this could be the RF parameter from the output of an RF        generator. Output power may be distinguished from input power of        an actuator producing the output. For example, an RF generator        may produce an output power of 1000 W as specified by the        recipe, but the input power suggested by the generator may be        significantly higher due to inefficiency of the generator.    -   3. Convert the recipe step output value to component output        power (if desired). If the recipe controlled parameter is        temperature, for example, but the actuation parameter is power        to a heater, the recipe output parameter may be converted into        the power suggested to maintain the specified temperature. This        may be done empirically by observing power vs. temperature        relationships for a process. It could also be implemented in        some cases by a computational thermodynamic model or other        computational physical model in the eco-efficiency analyzer.    -   4. Determine output power percentage by referring to component        full power output specification.    -   5. Determine component efficiency at recipe step output power by        referring to component efficiency curve (output as a percent of        input).    -   6. Calculate component input power requirements for the recipe        step.    -   7. Multiply by recipe step time and repeat factor (e.g., how        many times a recipe step should be repeated) to determine input        energy requirements for the recipe step    -   8. Add the step input energy requirements to the total        recipe-cycle input energy requirement.    -   9. Repeat from step 1 above until all recipe steps have been        analyzed and the total input energy for the equipment for one        recipe cycle has been determined.    -   10. Divide the total energy for one recipe cycle of n steps by        the execution time of the recipe cycle to obtain the average        input power requirement during execution of the recipe.        It should be noted that this example shows the calculation        method for a single recipe-controlled component. The method may        be extended to multiple components for each recipe step by        individually evaluating the output power and efficiency curve        for each component.

In one embodiment, the eco-efficiency characterizer for water usage maydetermine, based on the inputs specified for SEMI S23, the equivalentwater usage per-unit. Similarly, the remaining characterizers 204, 206may determine emissions per unit based on inputs of process gas andelectrical energy usages on a per-unit basis. Additionally, each of thecharacterizers 202-206 may determine, based on the inputs, a number ofequivalent environmental metrics using a set of environmental metricconversion factors. Factors for converting to these equivalent metricsmay be determined with reference to sources such as the Emissions andGeneration Resource Integrated Database (eGrid), for example.Environmental metrics may include, but are not limited to, globalwarming potential based on utility use on a per-unit basis and globalwarming potential based on emissions on a per-unit basis.

In one embodiment, combined eco-efficiency characterizer 208 may receiveas inputs the output characterizations of characterizers 202-206 todetermine a combined eco-efficiency characterization. In one embodiment,the combined eco-efficiency characterization is a single benchmarkcharacterization metric value that represents the eco-efficiency of themanufacturing equipment. In embodiments where an eco-efficiency metricis resource use or emissions per unit product, the lower theeco-efficiency value of the eco-efficiency metric, the better theeco-efficiency of the manufacturing equipment. Other embodiments mayinclude eco-efficiency metrics for which a higher value representsbetter eco-efficiency. An example of such an embodiment may bemanufacturing equipment that, as a by-product of its primary function,recovers waste heat energy. An eco-efficiency metric may be defined asheat energy recovered per unit product herein a higher value of themetric represents an increase in the eco-efficiency of the equipment. Inone embodiment demonstrating an improvement in eco-efficiency, aneco-efficiency value for electrical energy per-wafer consumption may be2.08 kWh per wafer pass. In another embodiment, an electrical energyeco-efficiency value for per-wafer consumption may be reduced to 1.9 kWhper wafer pass based on design and/or operational changes to themanufacturing tool. Similarly, equivalent industrial water use may bereduced from 2.1 to 1.9 L per wafer pass or emissions may be reducedfrom 0.07039 to 0.01689 kgCO₂e per wafer pass in order to effectimprovements in eco-efficiency. In other embodiments, the values foreco-efficiency metrics may be reduced (or increased) to and from anyother values. In one embodiment, the results of the per-uniteco-efficiency characterizations may be output on a graphical userinterface. Characterizations may be displayed in tables, graphs,topographical maps, or any other means of providing information on adisplay.

In one embodiment, eco-efficiency analyzer 104 provides functionality tocompare and contrast various versions of manufacturing equipment. Forexample, during the development and design stages of wafer manufacturingequipment, designers may create multiple versions (e.g., designs) of theequipment, perform per-unit eco-efficiency characterizations on eachversion, and compare the results. The design of the equipment may bereverted back to a prior saved design that has preferable eco-efficiencycharacteristics. Various subcomponents may have differenteco-efficiencies, and those eco-efficiencies may be compared andcontrasted with respect to the system as a whole. For example, adesigner may, during the course of developing a new manufacturing tool,have the option to select from and include a variety of subcomponentsthat all perform the same function. The designer may compare thesystem's eco-efficiency using each of the subcomponents to determinewhich combination of subcomponents yields the most desirable systemeco-efficiency result.

All versions of the design and associated characterizations may be savedin a database for future analysis or use. During development, the inputsto the per-unit eco-efficiency characterization may be received from anexisting prototype of the wafer manufacturing equipment being designed.After characterization, designers have the ability to modify the designof the prototype and re-characterize the eco-efficiency to determine howbest to optimize the eco-efficiency of the equipment.

In another embodiment, eco-efficiency analyzer 104 may determine thatone or more adjustments may be made to the settings of manufacturingequipment. Such adjustments may increase the eco-efficiency of themanufacturing equipment. Eco-efficiency analyzer 104 may send theadjustments to the manufacturing equipment to be implemented.Furthermore, eco-efficiency analyzer 104 may receive two eco-efficiencycharacterizations, compare the two to determine which characterizationis associated with a better eco-efficiency, and display the results ofthe comparison on a GUI. In one other embodiment, eco-efficiencyanalyzer may provide design change recommendations based on thecomparison, in view of the second eco-efficiency characterization beingassociated with a higher eco-efficiency characterization than the firstcharacterization.

FIG. 2B is a block diagram of an equipment controller 114, in accordancewith an embodiment of the present invention. In one embodiment,equipment controller 114 includes eco-efficiency characterizer 216,including utility use data analyzer 210 and utilization data analyzer212, and eco-efficiency controller 214. In one embodiment, manufacturingequipment 112 includes equipment controller 114. This arrangement of theutility usage data analyzer 210, the utilization data analyzer 212 andthe eco-efficiency controller 214 may be a logical separation, and inother embodiments, these modules or other components can be combinedtogether or separated into further components.

The modules of equipment controller 114 may be integrated intomanufacturing equipment 112 to provide automatic real-time monitoring,reporting, and optimization of the eco-efficiency of manufacturingequipment 112 while the equipment is in operation.

In one embodiment, eco-efficiency characterizer 216 performs theper-unit eco-efficiency characterization functionality of characterizers202-208 of FIG. 2A. An initial eco-efficiency model may be stored inequipment controller 114. This initial eco-efficiency model may be basedon predicted utility use data and/or predicted usage data. However, theactual utility use data and equipment usage data may differ from thepredicted data. Utility use analyzer 210 may determine an actual amountof utilities being used by the associated manufacturing equipment whilein operation. Worth noting is that while eco-efficiency characteristicsmay have been determined for the manufacturing equipment while indevelopment, designers may have estimated inputs (e.g., utility usevalues) for the characterization. While the manufacturing equipment isin operation, the inputs may be different than the estimated values usedin design. An eco-efficiency characterization performed by themanufacturing equipment, using actual utility use values, may help tomore accurately characterize the per-unit eco-efficiency of themanufacturing equipment.

The utilization data analyzer 212 may determine the utilization of theassociated manufacturing equipment. Utilization may be the ratio of thetime the equipment is operating to the time it remains idle. In oneembodiment, utilization is expressed as a percentage of the time theequipment is operational (e.g., actively manufacturing wafers). In oneembodiment, default utilization may be: 70% operational time, 25% idletime, and 5% time not consuming any utilities (e.g., the equipment isoff). In other embodiments various other utilization time values may beused. Utilization data may also include information about throughput(product units/time) and the product itself such as wafer size, numberof devices per wafer, etc. The latter information may be used tocalculate characterizations per unit other than wafer-pass (e.g., perdevice).

Using the utility and utilization information of 210 and 212,eco-efficiency characterizer 216 may determine the eco-efficiencycharacteristics of the associated manufacturing equipment.

In one embodiment, eco-efficiency characterizer 216 may compare measuredutility use data and utilization use data to the predicted utility andutilization use data used to determine the original eco-efficiencycharacteristics of the manufacturing equipment. A new eco-efficiencycharacterization may be calculated based on the actual utility use dataand utilization data recorded by the manufacturing equipment.Differences between the two eco-efficiency characterizations mayindicate that the manufacturing equipment may be further optimized foreco-efficiency by adjusting settings related to the manufacturingequipment. In one embodiment, new eco-efficiency characterizations maybe determined for each of emissions, electrical energy, and watereco-efficiency. A new combined eco-efficiency characterization mayadditionally be determined. In this way, actual eco-efficiency of amanufacturing equipment may be directly compared to theoreticaleco-efficiency for the manufacturing equipment determined during thedesign states of the equipment.

These new eco-efficiency characterizations may be determined byeco-efficiency analyzer 104 and sent to the equipment controller 114 tobe used to update the eco-efficiency characteristics for the associatedmanufacturing tool. New eco-efficiency characterizations determined byeco-efficiency analyzer 104 may also be sent to subcomponents of amanufacturing tool to be updated. Manufacturing tools and subcomponentsmay send updates to other tools and subcomponents that use the tools andsubcomponents in similar ways. Furthermore, eco-efficiencycharacterization updates and/or updated settings may be sent to andstored in a database for future use in manufacturing tool andsubcomponent design.

Based on the eco-efficiency characteristics determined by eco-efficiencycharacterizer 216, eco-efficiency controller 214 may determine andadjust settings of manufacturing equipment associated with equipmentcontroller 114 to better optimize the eco-efficiency of the equipment.In one embodiment, utility consumption may be reduced when manufacturingequipment is idle. Another embodiment may apply in the case where a“push-pull” actuation system is used, that is where, one actuator(generally cooling) operates primarily open loop while an opposingactuator (generally heating) operates closed loop to control thetemperature. By looking at the recipe and/or temperature sensors on theequipment to determine when periods of maximum cooling will and will notbe desired, the closed loop cooling system may be modulated bycontroller 214 to minimize cooling when maximum cooling is not desired(temperature ramp-up, extended periods of low power input to theprocess, etc.). This may reduce utility use by the cooling actuator andmay reduce utility use by optimizing the amount of heating input. Inother embodiments, other controller 214 may adjust other settings tooptimize eco-efficiency of the equipment.

In one embodiment, eco-efficiency controller 214 makes the changes tothe equipment settings automatically, without additional user input. Inanother embodiment, eco-efficiency controller 214 reports the results ofits analysis to a server to be further analyzed and acted upon. In oneembodiment, the modules of equipment controller 114 report theircharacterization results to a database, where the results may be used tobetter optimize the design of current and future manufacturingequipment.

FIG. 3 is a flow diagram illustrating a method for eco-efficiencycharacterization, in accordance with an embodiment of the presentinvention. The method 300 may be performed by processing logic thatcomprises hardware (e.g., circuitry, dedicated logic, programmablelogic, microcode, etc.), software (e.g., instructions run on aprocessing device to perform hardware simulation), or a combinationthereof. In one embodiment, characterizers 202-208 of eco-efficiencyanalyzer 104 executing on computing device 102 perform method 300.

Referring to FIG. 3, at block 301, processing logic receives a selectionof manufacturing equipment. In one embodiment, the selection is receivedfrom a graphical user interface (GUI). The selection may be manuallyinput directly into the GUI or selected from a database associated withthe GUI. When the selection is retrieved from a database with anassociated per-unit eco-efficiency characterization, a user may have theoption to accept the manufacturing equipment with correspondingcharacterization, select a different per-unit eco-efficiencycharacterization also associated with the manufacturing equipment, orperform a new per-unit eco-efficiency characterization for themanufacturing equipment. A user may choose to edit an existing per-uniteco-efficiency characterization for a retrieved manufacturing equipment.

At block 303, whether or not the manufacturing equipment selection wasinput manually or retrieved from a database, processing logic maydetermine utility use data associated with the manufacturing equipment.The utility use data may include direct water usage data, gas usagedata, and direct electrical energy usage data. The utility use data mayalso include other utility use data associated with, for example,cooling water, utility nitrogen, clean-dry/oil-free compressed air,exhaust, deionized/ultra-pure water and/or other liquid chemical usagedata, mechanical vacuum systems, and drain systems. The utility use datamay include actual data recorded from an existing manufacturingequipment, nominal values, predicted values, or estimated values. In oneembodiment, the manufacturing equipment is a prototype currently in adesign state of development. In such a case, estimated utility use datamay be received by processing logic. In another embodiment, utility usedata may be received that is associated with a manufacturing equipmentrelated to the equipment prototype.

At block 305, processing logic may receive utilization data associatedwith the manufacturing equipment. The utilization data may be associatedwith a processing time and an idle time of the manufacturing equipment.For example, utilization data may indicate that the selectedmanufacturing equipment is active 70% of the time while idle 25% of thetime, and off the remaining 5%. The utilization data may include actualdata recorded from an existing manufacturing equipment, nominal values,predicted values, or estimated values. Utilization data may also includedata associated with the process and product associated with themanufacturing equipment.

At blocks 307, 309, and 311, processing logic calculates a watereco-efficiency characterization, an emissions eco-efficiencycharacterization, and an electrical energy eco-efficiencycharacterization based on the utility use data and utilization data. Inone embodiment, process recipe data associated with a process beingperformed by the manufacturing equipment may also be used to calculatethe characterizations.

In one embodiment, at block 307, processing logic uses a set ofutilities requiring the use of water (e.g., cooling, nitrogen, exhaust,vacuum, etc.) to calculate an equivalent water use characterization,that is, the amount of industrial water needed to provide thoseutilities. Similarly, processing logic at block 311 calculates anequivalent electrical energy characterization giving the estimatedelectrical energy used to provide the utilities. At block 309,processing logic may use gas usage and utilization data to calculate anemissions characterization (pre- and post-abatement). Waste streams suchas heavy metals, eutrophication agents, and ozone depleters may also beused to calculate the emissions characterization. All three of thesecharacterizations may be converted to equivalent CO₂ emissions units,and, once expressed in this common unit, summed to a singlecharacterization metric.

In one embodiment, all three characterizations are also based on theutilization data received at block 305. In one embodiment,characterizers 202-206 perform the first, second and third,characterizations in view of the methods and operations described withrespect to FIG. 2. The equivalent water, equivalent emissions, andequivalent electrical energy per-unit eco-efficiency characterizationscalculated in blocks 307-311 may be displayed on a GUI. Additionally,the water, emissions, and electrical energy per-unit eco-efficiencycharacterizations calculated in blocks 307-311 may be stored in adatabase for future use. In one embodiment, water and electrical energycharacterizations are based on water usage, electrical energy usage, andother data associated with, for example, cooling water, utilitynitrogen, clean-dry/oil-free compressed air, exhaust,deionized/ultra-pure water and/or other liquid chemical usage data,mechanical vacuum systems, and drain systems. Each of the theseutilities and systems may consume water and electricity. In oneembodiment, water usage is determined for the above utilities andsystems, summed, and provided to processing logic to perform watercharacterization. In another embodiment, the electrical energy usage isdetermined for the above utilities and systems, summed, and provided toprocessing logic to perform electrical energy usage characterization.

At block 313, processing logic calculates a combined eco-efficiencycharacterization based on the water, emissions, and electrical energyeco-efficiency characterizations and the utilization data. The water,emissions, electrical energy, and combined, eco-efficiencycharacterizations may be associated with a per-unit amount ofenvironmental impact generated by the manufacturing equipment, asdescribed with respect to FIG. 2. In one embodiment, a single per-uniteco-efficiency value is calculated at block 313. The value may beindicative of the combined eco-efficiency of the associatedmanufacturing equipment. In one embodiment, the higher the value of aneco-efficiency metric, the better the eco-efficiency of themanufacturing equipment. In other embodiments, the lower the value of aneco-efficiency metric, the better the eco-efficiency.

At block 315, processing logic may provide at least one of the water,emissions, electrical energy, and combined eco-efficiencycharacterizations for display by a GUI. In one embodiment, the water,emissions, electrical energy, and combined per-unit eco-efficiencycharacterizations are all displayed concurrently on the GUI. In otherembodiments, a user of the GUI may select characterizations to displayand compare.

FIG. 4 is a flow diagram illustrating a method for on-equipmenteco-efficiency characterization, in accordance with an embodiment of thepresent invention. The method 400 may be performed by processing logicthat comprises hardware (e.g., circuitry, dedicated logic, programmablelogic, microcode, etc.), software (e.g., instructions run on aprocessing device to perform hardware simulation), or a combinationthereof. In one embodiment, modules 210, 212, and 214 of equipmentcontroller 114 executing on manufacturing equipment 112 perform method300.

Referring to FIG. 4, at block 401, processing logic may receive apreviously determined eco-efficiency characterization of a manufacturingequipment. In one embodiment, the eco-efficiency characterization may bereceived from a database. In another embodiment, the eco-efficiencycharacterization is received from the manufacturing equipment itself.For example, a per-unit eco-efficiency characterization may have alreadybeen determined (by processing logic in FIG. 3, for example) anddownloaded to the manufacturing equipment.

At block 403 and 405, utility use data and utilization data isdetermined. In one embodiment, utility data includes water, gas, andelectrical energy usage data. Utility use data and utilization data maybe received from the manufacturing equipment itself. In one embodiment,the manufacturing equipment records and maintains record of utility andutilization use data. The utility and utilization use data may beuploaded to a database and/or received from a database by themanufacturing equipment. In one embodiment, the manufacturing equipmentis currently operating under a different set of conditions (recipeparameters, utility usage, utilization time, etc.) than the model set ofconditions specified when the original per-unit eco-efficiencycharacterization was determined. For example, the original set ofconditions may be associated with a model reference control system usedto minimize the use of utilities and maximize eco-efficiency of theequipment.

As discussed above with respect to FIG. 1, to determine that anadjustment to settings may be made to increase eco-efficiency of a tool,processing logic may determine that actual utility and utilization usedata does not match with utility and utilization use data used to makethe initial eco-efficiency characterization. In this scenario,processing logic may determine that actual eco-efficiency of themanufacturing tool is less than estimated eco-efficiency for the tooland that changes may be made to the manufacturing equipment thatincrease the eco-efficiency of the equipment.

At block 407, processing logic determines, based on the use data,utilization data, and eco-efficiency characterization that an adjustmentmay be made to one or more settings associated with the manufacturingequipment. The adjustment to the settings may increase theeco-efficiency of the manufacturing equipment. In one embodiment,processing logic determines a new per-unit eco-efficiencycharacterization based on the received use and utilization data of themanufacturing equipment. The previous per-unit eco-efficiencycharacterization may be compared to the new per-unit eco-efficiencycharacterization to determine which is more eco-efficient. The newper-unit eco-efficiency characterization and the results of thecomparison may be stored in a database for future use. At block 409,processing logic implements the determined adjustment to the settingsassociated with the manufacturing equipment. In one embodiment,processing logic at block 409 implements the determined adjustment tothe settings associated with the manufacturing equipment when the newsettings result in improved eco-efficiency and the settings can beimplemented without detrimental impact to relevant equipment performanceparameters.

FIG. 5 is a block diagram of multicomponent manufacturing equipmentsystem, in accordance with an embodiment of the present invention. Inone embodiment, a system (e.g., manufacturing equipment 112, 116 ofFIG. 1) includes multiple sub-systems (e.g. sub-fab auxiliary systems122-128 of FIG. 1) 504. Sub-systems 504 may alternatively be included aspart the equipment 112, 116 itself. Subsystems 504 may also includemultiple sub-components 506. In one embodiment, eco-efficiencycharacterizations for the system 502 may be determined by determiningeco-efficiency characterizations for all sub-systems 504 andsub-components 506 included in the system.

For example, sub-components 506 may receive inputs such as utility usedata and utilization data 508. Based on the inputs, an eco-efficiencycharacterization 512 may be determined for each of the sub-components506. Next, eco-efficiency characterizations 514 may be determined foreach sub-system 504 based on inputs 516 to the sub-systems 504 andsub-component inputs 508. Rolled-up summary of all inputs 518 mayinclude a summary of input data sets 516 and 508 used to determinesub-system eco-efficiency results 514. In another embodiment,sub-component eco-efficiency results 512 may be used to calculateeco-efficiency characterizations 514. Accordingly, eco-efficiency forthe sub-system may be determined based at least in part on theeco-efficiencies that have been computed for each of the sub-componentsthat make up the sub-system.

The eco-efficiency characterization of the system as a whole (e.g. amanufacturing tool) 524 may be determined based on a summary of allinputs to the system 522 including direct inputs to the system 520,inputs 516 to the sub-systems 504, and inputs 508 to the sub-components506 included in the system. Rolled-up summary of all inputs 522 mayinclude a summary of input data sets 520, 516 and 508 used to determinesystem eco-efficiency results 524. In another embodiment, sub-systemeco-efficiency results 514 and sub-component eco-efficiency results 512may be used to calculate eco-efficiency characterizations 524. In oneembodiment, sub-systems 504 and sub-components 506 may have a variety ofeco-efficiency characterizations based on their inputs 516, 508. In oneembodiment, sub-system and sub-component eco-efficiency results 512, 514may be used to calculate eco-efficiency characterizations 524. In such acase, eco-efficiency characterization for the systems as a whole may bedetermined based on not only which particular sub-systems andsub-components are used, but also based on changes to the eco-efficiencyof the sub-systems and sub-components based on changes to their inputs.

FIG. 6 is a block diagram of a per-unit eco-efficiency characterizationsystem, in accordance with an embodiment of the present invention. Inone embodiment, a recipe execution algorithm 601 may receivemanufacturing equipment utilization data 624 and process recipeinformation for the current active recipe on a manufacturing equipmentfrom a library of process recipes 603. Recipe execution algorithm mayalso receive structure information 617 for the manufacturing equipment.The structure information 617 may include specific sub-systems andsub-components included in the manufacturing equipment. Recipe executionalgorithm 601 may also receive component data 602 associate withcomponent information 618. The component data may include component datafor the sub-components as they are configured for the manufacturingequipment. Component data may include the output vs. input power ratioefficiency of the components that are controlled by recipes on the basisof their output powers. The component efficiency data may have beenpreviously generated for one or more of the sub-components.

Process recipe library 603 may include recipes manually input by a user,recipes parsed from equipment recipe files, and/or recipes directlyuploaded from manufacturing equipment. Recipes may include informationsuch as step/time data, process power data, process material use-rates,and/or mechanical motion data. In one embodiment, equipment efficiencydata may include equipment information manually input by a user and/orequipment information from an existing equipment specification database.

Recipe-dependent energy use 604 (determined by the recipe executionalgorithm 601) may be combined with non-recipe dependent utility useinformation 605 (e.g., the set of fab-provided facilities utilities usedby the equipment (electricity, cooling water, N2, CDA, exhaust, vacuum,etc.)) and manufacturing equipment utilization data 624 and analyzedaccording to an equivalent energy algorithm 606 and equivalent wateralgorithm 607, as discussed above, to determine the amount ofelectricity, water, and fuel to operate the manufacturing equipment 608.Similarly, a process type 609 (e.g., an X etch process type or a PVD Yprocess type) from the process recipe library 603 and recipe dependentprocess material use 610 from the recipe execution algorithm 601 may beinput to a process emissions algorithm 611 to determine unabated processemissions 608 from the manufacturing equipment. Furthermore, ifabatement is being used with respect to the manufacturing equipment, thetype of abatement 613 and the unabated process emissions may be inputinto an abatement algorithm 614 to determine abated process emissionsfor the manufacturing device. The abatement algorithm 614 may beassociated with destruction and removal efficiency (DRE) factors from aDRE database 615.

Electricity and fuel, industrial water, unabated process emissions, andabated process emissions 608, 614 may be compared to published valuesfor equivalent CO₂ emissions to determine equivalent CO₂ emissionsvalues for energy use 619, treatment and delivery of industrial water620, and global warming potential (emission values for greenhouse gases)621. These values may be summed to determine the total equivalent CO₂emissions from operating the manufacturing equipment using the specifiedrecipe 623 and under other non-recipe dependent conditions specified in605 and 624. This value may be normalized to units of value produced bythe manufacturing equipment (e.g., wafers, devices, unit area, etc.)with utilization data 624 from the manufacturing equipment to determinethe per-unit eco-efficiency 625 of the manufacturing equipment. It isworth noting that process 600 shows only one embodiment of processingthe results of algorithms 606, 607 and 611 to calculate a combinedeco-efficiency metric which is, in the case of this embodiment, totalequivalent CO₂ emissions. Other embodiments of the invention may combinethe results of the first, second and third characterizations of 606, 607and 611 in such a way as to calculate other single combinedeco-efficiency metrics.

FIG. 7 illustrates a diagram of a machine in the example form of acomputer system 700 within which a set of instructions, for causing themachine to perform any one or more of the methodologies discussedherein, may be executed. In alternative embodiments, the machine may beconnected (e.g., networked) to other machines in a LAN, an intranet, anextranet, or the Internet. The machine may operate in the capacity of aserver or a client machine in client-server network environment, or as apeer machine in a peer-to-peer (or distributed) network environment. Themachine may be a personal computer (PC), a tablet PC, a set-top box(STB), a Personal Digital Assistant (PDA), a cellular telephone, a webappliance, a server, a network router, switch or bridge, or any machinecapable of executing a set of instructions (sequential or otherwise)that specify actions to be taken by that machine. Further, while asingle machine is illustrated, the term “machine” shall also be taken toinclude any collection of machines that individually or jointly executea set (or multiple sets) of instructions to perform any one or more ofthe methodologies discussed herein.

The example computer system 700 includes a processing device (processor)702, a main memory 704 (e.g., read-only memory (ROM), flash memory,dynamic random access memory (DRAM) such as synchronous DRAM (SDRAM),double data rate (DDR SDRAM), or DRAM (RDRAM), etc.), a static memory706 (e.g., flash memory, static random access memory (SRAM), etc.), anda data storage device 718, which communicate with each other via a bus730.

Processor 702 represents one or more general-purpose processing devicessuch as a microprocessor, central processing unit, or the like. Moreparticularly, the processor 702 may be a complex instruction setcomputing (CISC) microprocessor, reduced instruction set computing(RISC) microprocessor, very long instruction word (VLIW) microprocessor,or a processor implementing other instruction sets or processorsimplementing a combination of instruction sets. The processor 702 mayalso be one or more special-purpose processing devices such as anapplication specific integrated circuit (ASIC), a field programmablegate array (FPGA), a digital signal processor (DSP), network processor,or the like. The processor 702 is configured to execute instructions 722for performing the operations and steps discussed herein.

The computer system 700 may further include a network interface device708. The computer system 700 also may include a video display unit 710(e.g., a liquid crystal display (LCD) or a cathode ray tube (CRT)), analphanumeric input device 712 (e.g., a keyboard), a cursor controldevice 714 (e.g., a mouse), and a signal generation device 716 (e.g., aspeaker).

The data storage device 718 may include a computer-readable storagemedium 728 on which is stored one or more sets of instructions 722(e.g., software) embodying any one or more of the methodologies orfunctions described herein, including eco-efficiency analyzer 104 asshown in FIG. 7. The instructions 722 may also reside, completely or atleast partially, within the main memory 704 and/or within the processor702 during execution thereof by the computer system 700, the main memory704 and the processor 702 also constituting computer-readable storagemedia. The instructions 722 may further be transmitted or received overa network 106 via the network interface device 708.

In one embodiment, the instructions 722 include instructions forintegrating per-unit eco-efficiency characterization and/or a softwarelibrary containing methods that call an eco-efficiency analyzer 104including instructions for per-unit eco-efficiency characterization.While the computer-readable storage medium 728 (machine-readable storagemedium) is shown in an example embodiment to be a single medium, theterm “computer-readable storage medium” should be taken to include asingle medium or multiple media (e.g., a centralized or distributeddatabase, and/or associated caches and servers) that store the one ormore sets of instructions. The term “computer-readable storage medium”shall also be taken to include any medium that is capable of storing,encoding or carrying a set of instructions for execution by the machineand that cause the machine to perform any one or more of themethodologies of the present invention. The term “computer-readablestorage medium” shall accordingly be taken to include, but not belimited to, solid-state memories, optical media, and magnetic media.

In the foregoing description, numerous details are set forth. It will beapparent, however, to one of ordinary skill in the art having thebenefit of this disclosure, that the present invention may be practicedwithout these specific details. In some instances, well-known structuresand devices are shown in block diagram form, rather than in detail, inorder to avoid obscuring the present invention.

Some portions of the detailed description have been presented in termsof algorithms and symbolic representations of operations on data bitswithin a computer memory. These algorithmic descriptions andrepresentations are the means used by those skilled in the dataprocessing arts to most effectively convey the substance of their workto others skilled in the art. An algorithm is here, and generally,conceived to be a self-consistent sequence of steps leading to a desiredresult. The steps are those requiring physical manipulations of physicalquantities. Usually, though not necessarily, these quantities take theform of electrical or magnetic signals capable of being stored,transferred, combined, compared, and otherwise manipulated. It hasproven convenient at times, for reasons of common usage, to refer tothese signals as bits, values, elements, symbols, characters, terms,numbers, or the like.

It should be borne in mind, however, that all of these and similar termsare to be associated with the appropriate physical quantities and aremerely convenient labels applied to these quantities. Unlessspecifically stated otherwise as apparent from the following discussion,it is appreciated that throughout the description, discussions utilizingterms such as “receiving”, “determining”, “calculating”, “providing”,“sending,” “storing,” “comparing,” “modifying,” or the like, refer tothe actions and processes of a computer system, or similar electroniccomputing device, that manipulates and transforms data represented asphysical (e.g., electronic) quantities within the computer system'sregisters and memories into other data similarly represented as physicalquantities within the computer system memories or registers or othersuch information storage, transmission or display devices.

The present invention also relates to an apparatus for performing theoperations herein. This apparatus may be constructed for the intendedpurposes, or it may comprise a general purpose computer selectivelyactivated or reconfigured by a computer program stored in the computer.Such a computer program may be stored in a computer readable storagemedium, such as, but not limited to, any type of disk including floppydisks, optical disks, CD-ROMs, and magnetic-optical disks, read-onlymemories (ROMs), random access memories (RAMs), EPROMs, EEPROMs,magnetic or optical cards, or any type of media suitable for storingelectronic instructions.

It is to be understood that the above description is intended to beillustrative, and not restrictive. Many other embodiments will beapparent to those of skill in the art upon reading and understanding theabove description. The scope of the invention should be determined withreference to the appended claims, along with the full scope ofequivalents to which such claims are entitled.

What is claimed is:
 1. A method comprising: determining, by a processingdevice, a first eco-efficiency characterization associated with a firstdesign of manufacturing equipment based on one or more of watereco-efficiency characterization, emissions eco-efficiencycharacterization, or electrical energy eco-efficiency characterization,wherein the water eco-efficiency characterization, the emissionseco-efficiency characterization, the electrical energy eco-efficiencycharacterization, and the first eco-efficiency characterization areassociated with an amount of environmental impact generated by themanufacturing equipment per unit product produced by the manufacturingequipment; comparing the first eco-efficiency characterization to asecond eco-efficiency characterization that is associated with a seconddesign of the manufacturing equipment; and implementing the seconddesign of the manufacturing equipment responsive to determining, basedon the comparing, that the second eco-efficiency characterization isassociated with a lower amount of environmental impact per unit productthan the first eco-efficiency characterization.
 2. The method of claim1, wherein the first eco-efficiency characterization is furtherassociated with an amount of environmental resources consumed per unitproduct produced by the manufacturing equipment, wherein the secondeco-efficiency characterization is further associated with a loweramount of environmental resources consumed per unit product than thefirst eco-efficiency characterization.
 3. The method of claim 1, whereinthe second design of the manufacturing equipment is associated with oneor more of component selection, subsystem design, system integration,process design, process materials selection, or system configuration. 4.The method of claim 1, wherein the first eco-efficiency characterizationis based on a first overall eco-efficiency model of the first designbased on a first plurality of eco-efficiency models corresponding to afirst plurality of subcomponents of the first design, wherein the secondeco-efficiency characterization is based on a second overalleco-efficiency model of the second design based on a second plurality ofeco-efficiency models corresponding to a second plurality ofsubcomponents of the second design.
 5. The method of claim 1, whereinthe first eco-efficiency characterization and the second eco-efficiencycharacterization are associated with a first application of themanufacturing equipment, the method further comprising comparing a thirdeco-efficiency characterization of the manufacturing equipment and afourth eco-efficiency characterization of the manufacturing equipment,wherein the third eco-efficiency characterization and the fourtheco-efficiency characterization are associated with a second applicationof the manufacturing equipment.
 6. The method of claim 1 furthercomprising; determining eco-efficiency of the manufacturing equipmentduring first operation of the manufacturing equipment based on thesecond design; determining one or more updates to the second design toincrease the eco-efficiency; and implementing the one or more updatesduring second operation of the manufacturing equipment to increase theeco-efficiency of the manufacturing equipment.
 7. The method of claim 1,wherein the environmental impact per unit product produced is determinedon a per-wafer-pass basis of the manufacturing equipment.
 8. A systemcomprising: a memory; and a processing device coupled to the memory, theprocessing device to: determine a first eco-efficiency characterizationassociated with a first design of manufacturing equipment based on oneor more of water eco-efficiency characterization, emissionseco-efficiency characterization, or electrical energy eco-efficiencycharacterization, wherein the water eco-efficiency characterization, theemissions eco-efficiency characterization, the electrical energyeco-efficiency characterization, and the first eco-efficiencycharacterization are associated with an amount of environmental impactgenerated by the manufacturing equipment per unit product produced bythe manufacturing equipment; compare the first eco-efficiencycharacterization to a second eco-efficiency characterization that isassociated with a second design of the manufacturing equipment; andimplement the second design of the manufacturing equipment responsive todetermining, based on the comparing, that the second eco-efficiencycharacterization is associated with a lower amount of environmentalimpact per unit product than the first eco-efficiency characterization.9. The system of claim 8, wherein the first eco-efficiencycharacterization is further associated with an amount of environmentalresources consumed per unit product produced by the manufacturingequipment, wherein the second eco-efficiency characterization is furtherassociated with a lower amount of environmental resources consumed perunit product than the first eco-efficiency characterization.
 10. Thesystem of claim 8, wherein the second design of the manufacturingequipment is associated with one or more of component selection,subsystem design, system integration, process design, process materialsselection, or system configuration.
 11. The system of claim 8, whereinthe first eco-efficiency characterization is based on a first overalleco-efficiency model of the first design based on a first plurality ofeco-efficiency models corresponding to a first plurality ofsubcomponents of the first design, wherein the second eco-efficiencycharacterization is based on a second overall eco-efficiency model ofthe second design based on a second plurality of eco-efficiency modelscorresponding to a second plurality of subcomponents of the seconddesign.
 12. The system of claim 8, wherein the first eco-efficiencycharacterization and the second eco-efficiency characterization areassociated with a first application of the manufacturing equipment,wherein the processing device is further to compare a thirdeco-efficiency characterization of the manufacturing equipment and afourth eco-efficiency characterization of the manufacturing equipment,wherein the third eco-efficiency characterization and the fourtheco-efficiency characterization are associated with a second applicationof the manufacturing equipment.
 13. The system of claim 8, wherein theprocessing device is further to: determine eco-efficiency of themanufacturing equipment during first operation of the manufacturingequipment based on the second design; determine one or more updates tothe second design to increase the eco-efficiency; and implement the oneor more updates during second operation of the manufacturing equipmentto increase the eco-efficiency of the manufacturing equipment.
 14. Thesystem of claim 8, wherein the environmental impact per unit productproduced is determined on a per-wafer-basis of the manufacturingequipment.
 15. A non-transitory machine-readable storage mediumincluding instructions that, when accessed by a processing device, causethe processing device to: determine a first eco-efficiencycharacterization associated with a first design of manufacturingequipment based on one or more of water eco-efficiency characterization,emissions eco-efficiency characterization, or electrical energyeco-efficiency characterization, wherein the water eco-efficiencycharacterization, the emissions eco-efficiency characterization, theelectrical energy eco-efficiency characterization, and the firsteco-efficiency characterization are associated with an amount ofenvironmental impact generated by the manufacturing equipment per unitproduct produced by the manufacturing equipment; compare the firsteco-efficiency characterization to a second eco-efficiencycharacterization that is associated with a second design of themanufacturing equipment; and implement the second design of themanufacturing equipment responsive to determining, based on thecomparing, that the second eco-efficiency characterization is associatedwith a lower amount of environmental impact per unit product than thefirst eco-efficiency characterization.
 16. The non-transitorymachine-readable storage medium of claim 15, wherein the firsteco-efficiency characterization is further associated with an amount ofenvironmental resources consumed per unit product produced by themanufacturing equipment, wherein the second eco-efficiencycharacterization is further associated with a lower amount ofenvironmental resources consumed per unit product than the firsteco-efficiency characterization.
 17. The non-transitory machine-readablestorage medium of claim 15, wherein the second design of themanufacturing equipment is associated with one or more of componentselection, subsystem design, system integration, process design, processmaterials selection, or system configuration.
 18. The non-transitorymachine-readable storage medium of claim 15, wherein the firsteco-efficiency characterization is based on a first overalleco-efficiency model of the first design based on a first plurality ofeco-efficiency models corresponding to a first plurality ofsubcomponents of the first design, wherein the second eco-efficiencycharacterization is based on a second overall eco-efficiency model ofthe second design based on a second plurality of eco-efficiency modelscorresponding to a second plurality of subcomponents of the seconddesign.
 19. The non-transitory machine-readable storage medium of claim15, wherein the first eco-efficiency characterization and the secondeco-efficiency characterization are associated with a first applicationof the manufacturing equipment, wherein the processing device is furtherto compare a third eco-efficiency characterization of the manufacturingequipment and a fourth eco-efficiency characterization of themanufacturing equipment, wherein the third eco-efficiencycharacterization and the fourth eco-efficiency characterization areassociated with a second application of the manufacturing equipment. 20.The non-transitory machine-readable storage medium of claim 15, whereinthe processing device is further to: determine eco-efficiency of themanufacturing equipment during first operation of the manufacturingequipment based on the second design; determine one or more updates tothe second design to increase the eco-efficiency; and implement the oneor more updates during second operation of the manufacturing equipmentto increase the eco-efficiency of the manufacturing equipment.